Declarative Process Mining for DCR Graphs

Søren Debois; Thomas T. Hildebrandt; Paw Høvsgaard Laursen; Kenneth Ry Ulrik

doi:10.1145/3019612.3019622

Declarative Process Mining for DCR Graphs

Søren Debois
, Thomas T. Hildebrandt
, Paw Høvsgaard Laursen
, Kenneth Ry Ulrik

Programming Logic and Semantics

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.

Original language	English
Title of host publication	Proceedings of the Symposium on Applied Computing : SAC '17
Number of pages	6
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery
Publication date	2017
Pages	759-764
ISBN (Print)	978-1-4503-4486-9
DOIs	https://doi.org/10.1145/3019612.3019622
Publication status	Published - 2017
Event	The 32nd ACM SIGAPP Symposium On Applied Computing - Duration: 4 Apr 2017 → … Conference number: 32

Conference

Conference	The 32nd ACM SIGAPP Symposium On Applied Computing
Number	32
Period	04/04/2017 → …

Keywords

DCR graphs, declarative process mining

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10.1145/3019612.3019622

p759-deboisFinal published version, 754 KB

http://doi.acm.org/10.1145/3019612.3019622

Cite this

@inproceedings{089a208781464cef95818c41d9b8e227,

title = "Declarative Process Mining for DCR Graphs",

abstract = "We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.",

keywords = "DCR graphs, declarative process mining, DCR graphs, declarative process mining",

author = "S{\o}ren Debois and Hildebrandt, \{Thomas T.\} and Laursen, \{Paw H{\o}vsgaard\} and Ulrik, \{Kenneth Ry\}",

year = "2017",

doi = "10.1145/3019612.3019622",

language = "English",

isbn = "978-1-4503-4486-9",

pages = "759--764",

booktitle = "Proceedings of the Symposium on Applied Computing",

publisher = "Association for Computing Machinery",

address = "United States",

note = "The 32nd ACM SIGAPP Symposium On Applied Computing, SAC '17 ; Conference date: 04-04-2017",

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Declarative Process Mining for DCR Graphs. / Debois, Søren ; Hildebrandt, Thomas T.; Laursen, Paw Høvsgaard et al.
Proceedings of the Symposium on Applied Computing: SAC '17. New York, NY, USA: Association for Computing Machinery, 2017. p. 759-764.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

TY - GEN

T1 - Declarative Process Mining for DCR Graphs

AU - Debois, Søren

AU - Hildebrandt, Thomas T.

AU - Laursen, Paw Høvsgaard

AU - Ulrik, Kenneth Ry

N1 - Conference code: 32

PY - 2017

Y1 - 2017

N2 - We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.

AB - We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.

KW - DCR graphs, declarative process mining

U2 - 10.1145/3019612.3019622

DO - 10.1145/3019612.3019622

M3 - Article in proceedings

SN - 978-1-4503-4486-9

SP - 759

EP - 764

BT - Proceedings of the Symposium on Applied Computing

PB - Association for Computing Machinery

CY - New York, NY, USA

T2 - The 32nd ACM SIGAPP Symposium On Applied Computing

Y2 - 4 April 2017

ER -

Declarative Process Mining for DCR Graphs

Abstract

Conference

Keywords

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